Enabling demand response for optimal deployment of multi-carrier microgrids incorporating incentives
IET Renewable Power Generation, ISSN: 1752-1424, Vol: 16, Issue: 3, Page: 547-564
2022
- 11Citations
- 36Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This paper inspects customer multi-carrier microgrid deployments' techno-economic viability and assists investors in deciding whether or not to invest in multi-carrier microgrid installations equipped with smart demand-side technologies. The solution of the proposed model determines the optimal mix and size of distributed energy resources, and identifies the ideal participation rate of potential responsive customers within the multi-carrier microgrid. The objective of the proposed model is to minimize the overall deployment cost comprising the investment and replacement of distributed energy resources, demand-side smart measurement and informing appliances, loan payoff, operation, maintenance, peak demand charge, energy demand shifting reward or penalty, emission, and unserved energy while ensuring the desired levels of reliability and online reserve. The model also considers incentive policies to encourage customers to install demand-side smart technologies to participate in demand response programs actively. The planning problem is formulated by mixed-integer programming. The proposed model is applied to an industrial zone as an aggregate load. Numerical simulations exhibit the model's efficacy and scrutinize in-depth, the effect of a variety of factors on multi-carrier microgrid planning results, including the extents of the capital investment fund and loan in addition to demand response enabling technology cost.
Bibliographic Details
Institution of Engineering and Technology (IET)
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